There is a need to detect and identify unknown microscopic particles (e.g. no more than about 25 microns diameter) such as pathogenic microorganisms in fluid such as water or air. Protozoan parasites such as Cryptosporidium parvum, and Giardia lamblia are involved in water born outbreaks of disease, as they are present in the effluent of even state-of-the-art water treatment plants complying with current regulations. Current water quality monitoring techniques can take at least a day for results, are labor intensive and expensive, and have an unacceptably poor accuracy of identification. These monitoring techniques include immuno-fluorescence assay (IFA) and flow cytometry cell sorting (FCCS), as well as new techniques such as DNA Microarrays.
Attempts to monitor water for the presence and identity of microorganisms by optical techniques has met with mixed success. Although the presence of particles is readily detected by these techniques, it is difficult to identify the particles. In a technique in which one of the present inventors was an inventor, described in U.S. Pat. No. 4,548,500, microscopic particles of regular geometric shape were identified. That technique called Multi-Angle Light Scattering (MALS) used an approach called xe2x80x9cstrip maps.xe2x80x9d Simple particles such as homogeneous and isotropic spheres, homogeneous rods, and homogeneous ellipsoids were identified using optical data generated solely from the differential cross section (the angular dependence of the scattering amplitude). However, the strip map technique is limited to simple geometric structures.
In another test (described in an article by P. G. Wyatt and C. Jackson, Limnology and Oceanography, January 1989, pp. 96-112) detectors all lying in one plane were used to detect light scatter from twelve different species of phytoplankton in water. The scientists observed that the light scatter patterns for the difference species appear to be generally different. However, no way was known for using this data to identify an unknown particle as being a particular one of the twelve species or not any one of those species.
Although the identification of microorganisms in water is especially useful, it is also useful to be able to identify microorganisms in air, which may be pathogens spread by accident or deliberately by terrorists.
In accordance with one embodiment of the present invention, a method and apparatus are provided for the identification of unknown microscopic particles contained in a fluid such as water. The apparatus includes a source for generating a beam of energy such as a light beam from a laser. Fluid that contains particles is flowed through a detect zone lying along the laser beam. A plurality of detectors detect light scattered or otherwise dispersed (diffracted, refracted and transmitted) by a particle to the multiple locations of the detectors. A particle passing through the detect zone is an xe2x80x9ceventxe2x80x9d. The outputs of the multiple detectors, as a result of an unknown particle passing through the detect zone, represent an unknown subpattern, or eventvector. The unknown eventvector is compared with the multiple eventvectors obtained by detecting particles of a number of known species. If the eventvector for the unknown particle fits into one of the groups of eventvectors of a known specie of particle, then the unknown particle is deemed to be that specie of known particle.
A first step is to obtain multiple light scatter eventvectors for particles that are all of the same known specie. This is repeated for several different known species. The eventvectors are then analyzed using an algorithm that clusters the eventvectors, so as to group all eventvectors representing particles of the same specie as closely as possible, while separating groups of eventvectors representing particles of different species as far apart as possible. When an unknown particle is detected, its eventvector is compared to the eventvectors of those of a known specie. If the eventvector for the unknown particle lies within a volume that contains all retained eventvectors of a known specie of particles or lies is within a certain distance of the group of eventvectors of a known specie of particle, then the unknown particle is deemed to belong to that known particle class. Otherwise, the unknown particle cannot be identified.
Applicant prefers to use the MANOVA (Multiple Analysis of Variance) technique that analyzes data with a computer program that performs the above process.
The novel features of the invention are set forth with particularity in the appended claims. The invention will be best understood from the following description when read in conjunction with the accompanying drawings.